In vitro maturation and surrogacy in patients with vascular-type Ehlers–Danlos syndrome – A safe assisted reproductive technology approach
Bibliographic record
Abstract
Ehlers-Danlos syndrome (EDS) is an autosomal dominant connective tissue disorder with one of the highest maternal mortality rates of any condition. Patients with the vascular type of EDS are prone to spontaneous arterial and visceral ruptures. The occurrence of these severe and life-threatening complications is increased in pregnancy. Moreover, these patients carry a 50% risk of having an affected child. However, little is known about the risks of assisted conception treatments on these patients. We present the case of a 33-year-old woman suffering from EDS with a history of repeated ruptures of arterial aneurysms and a recently ruptured aneurysm of the splenic artery during her first intracytoplasmic sperm injection (ICSI) cycle who was then advised to undergo only unstimulated cycles. After a few natural ICSI cycles, the patient safely underwent two in vitro maturation cycles with pre-implantation genetic diagnosis in our unit. An unaffected blastocyst was transferred into a surrogate host. To our knowledge, this is the first case of EDS in assisted reproduction technologies including pre-implantation genetic diagnosis to be reported in the medical literature. This case has shown that unstimulated in vitro maturation and pre-implantation genetic diagnosis can safely be offered for vascular-type Ehlers-Danlos patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".